25 citations · 48 across the 4 of their papers we have counts for
4 papers
Efficient Vertical Federated Learning with Secure Aggregation
Xinchi Qiu, Heng Pan, Wanru Zhao +3
The majority of work in privacy-preserving federated learning (FL) has been focusing on horizontally partitioned datasets where clients share the same sets of features and can trai…
Secure Vertical Federated Learning Under Unreliable Connectivity
Xinchi Qiu, Heng Pan, Wanru Zhao +5
Most work in privacy-preserving federated learning (FL) has focused on horizontally partitioned datasets where clients hold the same features and train complete client-level models…
Gradient-less Federated Gradient Boosting Trees with Learnable Learning Rates
Chenyang Ma, Xinchi Qiu, Daniel J. Beutel +1
The privacy-sensitive nature of decentralized datasets and the robustness of eXtreme Gradient Boosting (XGBoost) on tabular data raise the needs to train XGBoost in the context of…
Touch and Go: Learning from Human-Collected Vision and Touch
Fengyu Yang, Chenyang Ma, Jiacheng Zhang +3
The ability to associate touch with sight is essential for tasks that require physically interacting with objects in the world. We propose a dataset with paired visual and tactile…